Emerging Technologies Work Group Master Data Management (MDM) in the Public Sector Don Hoag Manager.
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Transcript of Emerging Technologies Work Group Master Data Management (MDM) in the Public Sector Don Hoag Manager.
Emerging Technologies Work Group
Master Data Management (MDM) in the Public Sector
Don Hoag
Manager
Copyright © 2009 Deloitte Development LLC. All rights reserved.2
Emerging Technologies Work Group
Agenda
What is MDM?
What does MDM attempt to accomplish?
What are the approaches to MDM?• Operational• Analytical
Questions
Copyright © 2009 Deloitte Development LLC. All rights reserved.3
The characteristics of master data are:
• Shared across systems • Owned and governed by functional groups
• Fundamental to the proper execution • Uniquely identified entitiesof processes
While the above definition of master data may be acceptable, there are many different interpretations of master data
What is Master Data?
Point of View Enterprise Applications (SAP, Oracle)
MDM Vendors
Master Data elements Data elements that form the foundation of an organization’s processes that are in its enterprise systems
Reference data that is referred to by transactions and the system configuration
Data fields that are infrequently modified and shared throughout the enterprise
Common fields across all definitions
Customer name; program, service, and provider; customer Social Security Number, parent or legal guardian; service location’s address
Examples of differences Language code of user interface, flag to determine system feature enablement
System of origin description, time tag of field that was updated
“A process that spans an organization’s business processes and application systems, enabling the ability to create, store, maintain, exchange, and synchronize a consistent, accurate, and timely ‘system of record’ for core business. Addresses the harmonization and integrity of enterprise data which is vital to ensuring a consistent and complete view of business entities across the enterprise.” – Department of Public Welfare, Pennsylvania
Emerging Technologies Work Group
Copyright © 2009 Deloitte Development LLC. All rights reserved.4
Master Data — A Subset of Structured Data
Volume and
Volatility
Less
More
Semantics
More
Less
Types of Structured Data*
Metadata — Structure, meaning, and relationships of data. (column cusname stands for customer name and has a size of VARCHAR(50)).
Reference Data — Codes describing state and behavior of organization entities and transactions. (list of States, address types, etc.)
Enterprise Structure Data — Hierarchies within the enterprise (organization hierarchy)
Transaction Structure Data — Organization entities in which transactions act upon (customer data, provider data)
Transaction Activity Data — Operational transactions used in applications (case entries for a child welfare worker)
Transaction Audit Data — String of transactions executed to bring about a process flow (transaction logs showing execution of driver license creation)
* Source:BeyeNetwork, Malcolm Chrisholm
MD
M
Emerging Technologies Work Group
Copyright © 2009 Deloitte Development LLC. All rights reserved.5
Identifying Master Data Attributes
The scoring system can be used to assist in answering the question of whether data in question is master data
Identifying Master Data
Type of Attribute
Criteria Description Rating
Shared Is the data used by more than one business process/system?
0 – Data used in a single system/process1 – Data used by two systems/processes2 – Data used by more than two systems/processes
Value The element is fundamental to a business process, subject area, or business system.
0 – Data is useful to individuals only1 – Data is critical to a single business process2 – Data is critical to multiple business processes
Volatility Data modification behavior 0 – Transaction data 1 – Reference data2 – Data added to or modified frequently, but the data is not
transaction data
Total
Results0-2 Attribute is not master data (or any criteria is rated 0)3-4 If any criteria is rated 0, attribute is not considered master data. Otherwise, attribute minimally meets criteria for master data and further
investigation should be considered>4 Attribute is master data
There are also different categories of master data attributes.
Identifier — ID, Alternate IDs, Cross-reference.
Core — Core fields shared across many processes
Extended — Business process specific
Most MDM solutions manage identifier, core, and a subset of extended attributes
The differing definitions of master data make it challenging for governance organizations to determine what data elements qualify for management.
Emerging Technologies Work Group
Copyright © 2009 Deloitte Development LLC. All rights reserved.6
MDM
Enterprise Master Data
Vendor Employee Customer Provider Location Programs
Operational and Transactional Processes
Business Intelligence
Data Q
uality
What Is MDM ?
Efficiencies From MDM
Decision Support Benefits From MDM
• A maintainable “system of record” for core business entities
• The single source for core business entities for the enterprise
• Improved data management resulting in better performance
• Increased efficiencies resulting from reduced data error
• Increased confidence in decisions resulting from better understanding of data
• Reduced risk
Child Welfare Medicaid Motor VehiclesD
ata
Go
vern
ance
MDM is accomplished through the implementation of an overarching governance structure, business processes, data organization, data architecture, and enabling technology.
Emerging Technologies Work Group
Insurance Child Support Financial
Copyright © 2009 Deloitte Development LLC. All rights reserved.7
Emerging Technologies Work Group
Approaches to MDM
Given the nature of MDM and the various groups promoting its efficacy, there are several approaches to its implementation:• Operational: An application- or system-based approach that attempts to
centralize and standardize the collection of subject area data into a single solution, to which other applications publish and subscribe.
• Analytical: A logical or physical data structure approach that attempts to centralize and standardize the view of subject area data into a single solution, with which users may see data that spans across applications or programs.
Copyright © 2009 Deloitte Development LLC. All rights reserved.8
Emerging Technologies Work Group
Operational MDM
People: Enterprise Architects (e.g., Architecture, Data, Software)
Process:• Gathering information about current data standards and usage in an organization from
documentation, application owners.
• Defining hierarchy of applications and their priority on updates
• Addressing anomalies and constraints – Lends to data governance discussions and data quality discussions
Technology:• New application development associated with primary subject areas (e.g., customer and
provider)
• Modification of existing systems to publish and subscribe
An application- or system-based approach that attempts to centralize and standardize the collection of subject area data into a single solution, to which other applications publish and subscribe.
Copyright © 2009 Deloitte Development LLC. All rights reserved.9
MDM Architecture — Hub and Spoke
• All or some of the master data is maintained centrally in a hub architecture
• System of record is put in place with respect to master data entities being maintained
• MDM related communication is channeled via the hub
• Allows for more effective policies around data standardization and deduplication can be put in place
• Foundations for governance of master data and associated processes become a reality
Centralized repository for customer, provider, program, and employee “master” data
Standard data entities, attributes, and business rules
MDM
Data management, stewardship, and governance processes
Business intelligence and reporting
Portals, extranets, Web services, and knowledge systems
Transaction systems, legacy repositories,
and applications
Services interface
Data interface
Reporting interface
Data Management
The Hub and Spoke integration approach is the most effective high level architecture approach used in MDM solutions today.
Emerging Technologies Work Group
Copyright © 2009 Deloitte Development LLC. All rights reserved.10
Emerging Technologies Work Group
Analytical MDM
People: Data Architects, Report Developers
Process:• Top-Down Approach for definition of Subject Areas
• Bottom-Up Approach for definition and conformance of Dimensions
Technology:• Unified modeling
• Data Dictionary/Metadata
• Extraction, Transformation and Loading (ETL) tools
A logical or physical data structure approach that attempts to centralize and standardize the view of subject area data into a single solution, with which users may see data that spans across applications or programs.
Copyright © 2009 Deloitte Development LLC. All rights reserved.11
Analytical Unified Modeling
MCI #First / Last NameDOBCitizenshipGenderDPW Sys Code
MCI #First / Last NameDOBRaceService Coord
MCI #PA Secure IDSchool DistrictPrimary LanguageGrade Level
Client IDFirst / Last NameDOBSexCase Worker
MCI #First / Last NameDOBCitizenshipGenderDPW Sys Code
MCI #First / Last NameDOBRaceService Coord
MCI #PA Secure IDSchool DistrictPrimary LanguageGrade Level
Client IDFirst / Last NameDOBSexCase Worker
MCI
HCSIS Consumer
ELN Client
PACSES Client
MCI_Landing
HCSIS_Consumer_Landing
ELN_Client_Landing
PACSES_Client_Landing
1 2 3
Recipient IDSource Sys IDSource Sys CodeFirst NameLast NameDOBCitizenshipGenderLanguageSource 1 FlagSource 2 FlagSource 3 FlagSource Counter
Recipient ID
Operational
Integrated
ODS_Recipient
Recipient IDClient IDCase Worker
PACSES_Recipient
1 1
Recipient IDMCI #PA Secure IDGrade Level
ELN_Recipient
1 1
Recipient IDMCI #Service Coord
HCSIS_Recipient
1
1
Recipient ID
Recipient ID
HCSIS_Case
ELN_Enrollment
PACSES_Case
4
5
6
Emerging Technologies Work Group
Integrating core data in a logical and physical environment for data analysis provides for a singular customer view across programs.
Copyright © 2009 Deloitte Development LLC. All rights reserved.12
Lessons Learned
Business value, leadership, and team
Scope, communications, and governance
Process and architecture
Our experiences with large master data management programs have provided us with many lessons learned.
Emerging Technologies Work Group
Copyright © 2009 Deloitte Development LLC. All rights reserved.13
Contact Information
Don Hoag
Deloitte
412-402-5292
Emerging Technologies Work Group